Dynamic Load Management for NG IPS Ships

Transcription

1 1 Dynamic Load Management for NG IS Ships Xianyong Feng, Student Member, IEEE, Tais Zourntos, Senior Member, IEEE, Karen L. Butler- urry, Senior Member, IEEE, and Salman Mashayeh, Student Member, IEEE Abstract A simplified notional Next Generation Integrated Shipboard ower System (NG IS) model is introduced. Based on the simplified system model, dynamic load management method is presented considering equality and inequality constraints of the system. The problem is formulated as a dynamic optimization problem to imize the energized loads in the system without violating any constraint of the system. A simplified NG IS model is simulated in SCAD, and three scenarios are presented to illustrate the dynamic load management method. The simulation results indicate that the dynamic performance of the shipboard power system model with load management is much better than its performance without load management. Index Terms Constant Load, Dynamic Load Management, ropulsion Load, SCAD, ulse Load, Shipboard ower System I I. INTRODUCTION N navy shipboard power systems, battle damage or sudden increase in load demand, such as pulse load and other weapon loads, can easily overload the generators. Moreover, shipboard power systems have less generation capacity and rotational inertia relative to system load [1] and include large portion of dynamic loads and nonlinear loads relative to power generation capacity [2]. Therefore, it is necessary to balance the load demand and generation power of the system in real time. Otherwise the system cannot operate normally, or it even causes some devastating impact on the ship s survivability. Therefore, an effective dynamic load management technique needs to be developed to match the load demand and generation power of the shipboard power system in real-time without violating operating constraints of the system. Load management was firstly introduced in 197s and aimed to control and modify the patterns of demands of various consumers of a power utility, which reduced the operating cost and maintained the reliability of the electric power networ. Load management can be categorized into direct load control (DLC), indirect load control, and local energy storage. DLC mainly focuses on shedding load directly to satisfy certain objectives; indirect load control allows customers control their loads independently according to the price signal sent by the utilities; local energy storage allows both utilities and customers store energy in off-pea periods and use the stored energy during times of great demand. Real- This wor was supported by Office of Naval Research under Grant N X. Feng, T. Zourntos, K. L. Butler-urry, and S. Mashayeh are with the Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 7784 USA ( [email protected], [email protected], [email protected], [email protected]). time load management mainly focuses on matching the generation power and the consumed loads in real-time while achieving certain objectives, such as reducing operating cost [3], imizing the profit margin [4], reducing pea load [3], etc. Since the control status and load profile of the power system can be accessed by the control center almost instantaneously, real-time load management techniques can be developed to optimally coordinate the most suitable customers for the direct load control [5]. Even though load management has been developed for more than 3 years, the techniques are mainly applied to solve the load control problem in terrestrial power systems. Since shipboard power systems have much faster transients, it is necessary to tae the dynamic characteristics of the system into consideration. Fortunately, concepts of real-time direct load control can be extended to shipboard power systems through including the system dynamics. If there is not enough generated power to serve all the loads in the system, only higher priority loads are energized and some non-vital loads are shed to avoid the generator overloading. The dynamic load management can be formulated as an optimization problem considering different load priorities. The objective of dynamic load management is to imize the energized loads in shipboard power systems in real-time without violating system operating constraints. In this paper, a simplified notional shipboard power system model is introduced. The simplified NG IS model includes generators, transformers, propulsion load, pulse load, and two zones. In each zone, different priority loads are considered. A new dynamic load management method is presented, which aims to imize the energized load subject to system constraints. Three case studies are presented to illustrate the dynamic performance of the dynamic load management. The simulation results using dynamic load management are compared to show the advantages of the load management approach. This paper is organized as follows: section II discusses the simplified notional shipboard power system model. Section III presents the dynamic load management method. Three case studies are presented in section IV. The summary is given in section V. The conclusions and future wor are given in section VI. II. NOTIONAL SHIBOARD OWER SYSTEM MODEL A simplified notional shipboard power system was modeled to illustrate the proposed dynamic load management method and study the dynamic performance of the system. The simplified notional shipboard power system includes one main turbine generator (MTG), one auxiliary turbine generator

2 2 L DC14 L DC11 L DC12 L AC13 L DC L DC21 L DC22 L AC23 Fig. 1. The diagram of simplified notional shipboard power system. (ATG), two 13.8/4.16 V transformers, one propulsion load, one pulse load, and two zones. The system also includes different inds of power electronic components, such as DC- DC converters, inverters, and rectifiers. In the simplified system, the influence of cables is not significant, so the cable model is neglected. The simplified notional shipboard power system diagram is shown in Fig. 1. The components definition is shown in Table I. The two transformers convert line-to-line voltage from 13.8 V to 4.16 V. Each zone has two DC distribution buses, a starboard side bus and a port side bus. The DC distribution buses on the same side are served by the same CM4, which converts 4.16 V 3-ph AC voltage to 1 V DC voltage. CM4 cannot serve starboard side bus and port side bus at the same time. The CM4-1 is serving the DC distribution buses on port side. The CM4-2 is serving the DC distribution buses on starboard side. And the capacity of each CM4 is 2 MW. Each DC distribution bus is connected to a CM1, which converts the 1 V DC voltage into three voltage levels, 375 V DC, 65 V DC, and 8 V DC. CM2 is connected to 8 V DC and inverts the 8 V DC to 3-ph 46V AC to serve AC loads. In each zone, different inds of loads are served by the DC distribution buses. These loads may have different voltage levels, different power levels, etc. In this simplified notional shipboard power system, all the DC loads in zones are constant resistance loads, and all the AC loads are constant power loads. In order to illustrate the dynamic load management method, load priorities need to be decided. Assume that LDC 12 and LDC 22 are vital loads; L DC 11, L DC 21, L AC 13, and L AC are semi-vital loads; L 23 DC and L 14 DC are non-vital loads. The load priority information is shown in Table II. The weight-factor of each load is chosen based on load priority definition in load management method. III. DYNAMIC LOAD MANAGEMENT METHOD The objective of dynamic load management is to serve as many loads as possible considering priorities subject to the constraints of system. If the available generation power is decreased, the system may not serve the same amount of loads TABLE I COMONENT DEFINITIONS No. Component Name Component Description 1 MTG 3 ph, 13.8 V, 36 MW generator 2 ATG 3 ph, 13.8 V, 4 MW generator 3 Transformer 1 3 ph, Δ-Δ connected, 13.8/4.16 V 4 Transformer 2 3 ph, Δ-Δ connected, 13.8/4.16 V 5 ulse Load 12 MW,.3 s pulse width, 4.16 V, AC 6 ropulsion Load 36.5 MW (rating), 4.16 V, AC 7.4 MW,.375 V DC 8.95 MW,.65 V DC 9.5 MW,.46 V AC 1.2 MW,.375V DC 11.4 MW,.375 V DC MW,.65 V DC 13.5 MW,.46 V AC 14.2 MW,.375V DC TABLE II LOAD RIORITY Load Weight Factor Load Type 1.5 Semi-vital 1.7 Vital 1.4 Semi-vital 1. Non-vital 1.5 Semi-vital 1.7 Vital 1.4 Semi-vital 1. Non-vital as before. In this case, load management needs to shed some non-vital loads in the system to mae the system operate normally without violating operating constraints of the system. However, that load shedding is the last resort in dynamic load management. In order to formulate dynamic load management, dynamic characteristics of the system should be taen into consideration. The dynamic load management problem can be formulated as an optimization problem. In normal state, the objective of load management is to imize capacity of the energized loads. Through controlling the status of load switches, the loads will be matched with the power generation in real-time and the power system should operate within the system operating constraints at the same time.

3 3 A. Objective Function The objective function of dynamic load management can be expressed as follows: y W (1) L where L is the load set in the power system, y (t) is the switching function, which has a value of or 1 ( y = 1 : load is connected to the power system at time t, y = : load is not connected to the system at time t), W is the weight-factor of load, and (t) is the consumed power by load, and can be determined using (8). In order to serve as many higher priority loads as possible, loads are categorized as vital, semi-vital and non-vital loads. In shipboard power systems, vital loads include combat systems, mobility systems, fire systems, navigation system, communication system, etc. Non-vital loads are those that can be shed during an electrical casualty [6]. A technique was developed in earlier wor for determining weight factor of shipboard power system loads [6], [7] as shown in (2)-(4). For vital load: Non + Semi W = + 1 (2) For semi-vital load: Non W = + 1 (3) For non-vital load: W = 1 (4) where W is weight-factor of load, Semi is equal to the imum value of the largest semi-vital load, and Non is equal to the imum value of the largest non-vital load in the system. The contribution ( T i ) of each vital load i in the objective function is given by [6]: Non Semi T i i Wi i + = = + 1 = Non + Semi + i (5) i The contribution ( T j ) of each semi-vital load j in the objective function is given by: Non T j j W j j = = + 1 = Non + j (6) j The contribution ( T ) of each non-vital load in the objective function is given by: T = W = 1 = (7) The total contribution of the vital load in the objective function is elevated by Non + Semi. As Non and Semi are the values of the largest semi-vital and non-vital load respectively, it can be seen that the contribution of each vital load will be greater than the contribution of each semi-vital or non-vital load. Therefore, all vital loads will be served before the semi-vital and non-vital loads. For the same reason, all semi-vital loads will be served before the non-vital loads. B. Load Model In this formulation, only constant resistance loads and constant power loads are considered. The constant resistance load model is expressed as follows: ( V ) 2 = (8) R where R is the resistance of the load, V (t) is the load voltage at time t, and (t) is the power consumed by the load. In the wor reported in this paper, all DC loads are constant resistance loads, and all AC loads are constant power loads. C. Equality Constraints The solution of dynamic load management should satisfy the system dynamic equations, which are represented by Differential-Algebraic Equations (DAEs) [1], [8] shown as follows: ( x( t), u( t), y) ( x( t), u( t), y) x& = f (9) = g where x (t) is the state vector of the system, u (t) is the vector of control input to the system, y is the vector of load switch states, f ( ) is the vector of system dynamic equations, g ( ) is the vector of system algebraic constraints. D. Inequality Constraints In addition to the equality constraint, the system should also satisfy operating inequality constraints. In the formulation, available power source capacity constraints, voltage limit constraints, flow constraints, and load constraints are considered as follows: 1) Constraint on Available ower Source Capacity: The sum of all bus loads and total losses of the power system should not be larger than the capacity of available power sources. The constraint can be expressed as follows: L y + t [, T ] losses G j j S (1) where losses (t) is the total losses of the power system at time t, G j (t) is the available power of generator j, and S is the set of generators in the system. 2) Voltage Limit Constraints: The voltage magnitudes should vary within certain limits, otherwise, most of the electric devices connected to the bus will not operate satisfactorily. A general expression for voltage constraints is shown as min Vm Vm Vm m { 1, 2, L, M } t [, T ] (11) where M is the total number of system buses, V m (t) is the min voltage magnitude at bus m, V m and V m are the minimum and imum tolerable voltage magnitudes at bus m, respectively. 3) Flow Constraints: The power flow in a branch should not exceed the capacity of the branch if the line is closed [9]. The power flow constraints on each branch are shown as follows:

4 4 lxy lxy C l B t [, T] (12) xy where l xy is the transmission line (cable) connecting bus x and y, C l xy is the power flow capacity of branch l xy, B is the set of directed branches (including all branches) of the system, l xy (t) is power flow on branch l xy. 4) Load Constraints: The total loads on bus should not exceed the power capacity of the bus. The load constraints are formulated as follows: C t [, T ] (13) L L where C is the power capacity of load bus, and (t) is the power consumed by load bus. IV. ILLUSTRATION OF DYNAMIC LOAD MANAGEMENT In this section, the dynamic load management is illustrated based on the simplified notional shipboard power system SCAD model. The objective is to imize the energized loads in shipboard power systems without violating available power source capacity constraint and CM4 capacity constraint. The CM4 capacity constraint means that the total loads connected to starboard (or port) side in zones should not exceed 2 MW. In case 1, the available power source capacity constraint is studied to show that the dynamic load management can eep the total load demand less than power generation capacity. In case 2, CM4 capacity constraint is illustrated to show that dynamic load management can mae the CM4 capacity constraint satisfied. In case 3, pulse load is considered in the system to show that dynamic load management can consider the pulse loads. Assume that the priority of propulsion loads is higher than that of loads in zones, which means that propulsion should be served before the loads in zones. Moreover, we assume the pulse loads have higher priority than propulsion loads, since most pulse loads are weapon loads, which have higher priority. In order to illustrate the load management method, the available power source capacity constraint and CM4 capacity constraint are considered. Therefore, the problem can be reformulated as shown in (14). y W s. t. L i i Starboard j j ort L 2 MW 2 MW y + losses l S G l (14) where, L is the load set in shipboard power system, Starboard is the set of loads served by starboard side DC distribution buses, ort is the set of loads served by port side DC distribution buses, and S is the set of available generators in the system. A. Case 1 In this case, the available power source capacity constraint is illustrated based on dynamic load management. The system dynamic performance without load management is studied firstly, and the available power source capacity constraint may be violated. Then the system with dynamic load management is studied to show that the available power capacity constraint is always satisfied. In case 1, MTG generator was connected, and ATG generator was out of service. Thus, the generation capacity was 36 MW. The power demand of propulsion load was increased from 3.5 MW to 32.5 MW at 8 s, and decreased from 32.5 MW to 3.5 MW at 11 s. In zones, L DC was not served, and L DC, L 11 DC, L 12 DC, L 21 DC, L 22 AC, L 13 AC, and 23 LDC 14 were served, where, LDC and L 12 DC were served by 22 port side DC distribution buses, and the other loads were served by starboard side DC distribution buses. The load demand in the two zones was 3.9 MW. Therefore, the load demand of the system was changed from 34.4 MW to 36.4 MW at 8 s, and the demand was returned to 34.4 MW at 11 s. The total losses of the system were about 1.6 MW. The total load demand of the system includes the power consumed by loads and losses of the system. The forecasted load demand and generation capacity are shown in Fig. 2. The load status is shown in Table III. From 8 s to 11 s, the forecasted load exceeded the generation capacity. If load management method was not applied, the available power source capacity constraint was violated between 8 s and 11 s, which is shown in Fig. 3(a). The frequency of MTG generator was decreased from 6 Hz to 58.7 Hz at 8 s due to the increased load, and the frequency returned to 6 Hz after the load demand decreased at 11 s, which is shown in Fig. 3(b) Fig. 2. and generation capacity for case 1. TABLE III LOAD STATUS WITHOUT LOAD MANAGEMENT Time ~8 s 8~11 s 11~15 s served served served served served served served not served not served not served ulse Load not served not served not served ropulsion Load 3.5 MW 32.5 MW 3.5 MW

5 Total load demand 3 (a) Total load demand (b) MTG generator frequency Fig. 3. Dynamic performance of simulated model without load management. To improve the dynamic performance of the system model, the dynamic load management method was applied to the shipboard power system model to imize the energized load in real-time without violating operating constraints of the system. The forecasted load exceeded the generation capacity at 8s. In order to ensure that total consumed power was less than generation capacity, load management method was applied at 7.8 s to shed some lower priority loads in zones. The loads were shed based on the load priority to mae the objective function optimal. In this case, all non-vital and semivital loads L DC, L 11 DC, L 14 DC, L 21 AC, and L 13 AC were shed 23 which total 2 MW. Only the two vital loads LDC and L 12 DC22 were still served, which made the objective function optimal. Therefore, the total load demand was decreased from 38 MW to 36 MW. After 11 s, the power demand of the propulsion load was decreased from 32.5 MW to 3.5 MW. At 11.2 s, load management method was applied to restore loads L DC 11, L DC 14, L DC, L 21 AC, and L 13 AC, which were shed at 7.8 s. The 23 load status of the system is shown in Table IV. Fig. 4(a) indicates that the generation power does not exceed the capacity of the generation except several spies. After shed 2 MW loads at 7.8 s, the frequency began to increase slowly, and then the propulsion load increased to 32.5 MW, so the frequency was maintained at 6 Hz, which is shown in Fig. 4(b). At 11 s, the total load demand was decreased to 34 MW, and the loads were restored after.2 s. In this period, the frequency changed in the range of.9 Hz to 6. Hz. The load management method began to wor before the total load demand exceeded the generation capacity, which prevented the frequency of MTG dropping. After shedding 2 MW loads in the zones, the total load demand in the system was decreased to about 36 MW, which satisfied the available power source constraint. The voltage of Load L DC is shown in Fig. 5. This load 11 was shed at 7.8 s and restored at 11.2 s. Therefore, the voltage of L DC was zero between 7.8 s and 11.2 s. The input voltage 11 of CM2-1 in zone 1 is shown in Fig. 6. The voltage was also zero between 7.8s and 11.2s. The voltage of Load L DC is 12 shown in Fig. 7. This load had highest priority in the system, and was not shed. Thus, the voltage was always ept at 65 V. The voltage of Load L DC is shown in Fig. 8. This load had 14 lowest priority in the system, and was shed at 7.8 s and restored at 11.2 s. Thus, the voltage of L DC was between s and 11.2 s. TABLE IV LOAD STATUS WITH LOAD MANAGEMENT Time ~7.8 s 7.8~8 s 8~11 s 11~11.2 s 11.2~15 s served served not served not served not served not served not served ulse Load not served not served not served not served not served ropulsion Load 3.5 MW 3.5 MW 32.5 MW 3.5 MW 3.5 MW Total load demand (a) Total load demand 57 (b) MTG generator frequency Fig. 4. Dynamic performance of simulated model with load management.

6 6 L DC Fig. 5. Voltage of t (s) t (s) Fig. 6. Input voltage of CM2-1 in Zone 1. L DC t (s) constraint. If the CM4 capacity constraint was not considered, all the loads in zones can be served, since the total power demand by the loads in zones was 4.1 MW. Firstly, all the loads in zones were connected to the system. The two vital loads were connected to port side DC distribution buses, and the other loads were connected to starboard side DC distribution buses. The load status of the system is shown in Table V. The input power to CM4-1 and CM4-2 is shown in Fig. 9 and Fig. 1, respectively. The input power to CM4-1 did not exceed the capacity of CM4. However, the input power to CM4-2 exceeded the capacity of CM4, which meant that the CM4 capacity constraint was violated in this case. In order to handle this problem, the load management method was applied. L DC is non-vital load and has the lowest priority. Thus, L DC was shed at 2 s to reduce the input power to CM4-2 and mae the objective function optimal. The load status of the system is shown in Table VI. TABLE V LOAD STATUS WITHOUT LOAD MANAGEMENT Time ~2 s 2~5s ulse Load not served not served ropulsion Load 25 MW 25 MW Fig. 7. Voltage of Capacity of CM4 Input power to CM4-1 L DC t (s) Fig. 8. Voltage of. B. Case 2 In this case, the CM4 capacity constraint is illustrated to show that the dynamic load management method can mae the CM4 capacity constraint satisfied. The propulsion load was set to 25 MW. The total capacity of the system was 4 MW by assuming that MTG generator and ATG generator were both available. Thus, the system can still serve another 15 MW loads without violating the available power source capacity Fig. 9. The input power to CM4-1 without load management Capacity of CM4 Input power to CM Fig. 1. The input power to CM4-2 without load management.

7 7 Fig. 11 shows that the CM4 capacity constraint is satisfied after shedding L DC. The transients from 2 s to 2.5 s were caused by the switch changes of DC-DC converter in CM1. C. Case 3 In case 3, a 12 MW pulse load was incorporated into the system model. In the simplified notional shipboard power system, the pulse load was modeled as an AC constant power load, whose voltage level was 4.16 V. The pulse width of the load was.3 s and this load should be served at 1 s. In order to simplify the problem, only propulsion load and pulse load were considered, which meant that all the loads in zones were disconnected. In this case, MTG generator was available and ATG generator was out of service. Thus, the generation capacity of the system was 36 MW. The power demand of propulsion load was 3 MW and the pulse load was served from 1 s to 1.3 s. The total load demand exceeded the available power source capacity from 1 s to 1.3 s shown in Fig. 12 (a), so the frequency dropped from 6 Hz to.2 Hz, and the frequency returned to 6 Hz gradually after the pulse load was disconnected, which was shown in Fig. 12(b). Dynamic load management was applied to improve the dynamic performance of the system and mae the available power source capacity constraint satisfied. In order to ensure system constraints were satisfied, propulsion load should be adjusted from 3 MW to 18 MW, when the pulse load was served. Therefore, the propulsion load was decreased from 3 MW to 18 MW at 9.9 s, before pulse load served, and increased to 3 MW at 1.4 s, after the pulse load disconnected. Fig. 13(a) shows that total load demand is always less than generation capacity. The MTG generator frequency changes between.7 Hz and 6.2 Hz, which is shown in Fig. 13(b) TABLE VI LOAD STATUS WITH LOAD MANAGEMENT Time ~2 s 2~5s served shed ulse Load not served not served ropulsion Load 25 MW 25 MW Capacity of CM4 Input power to CM Fig. 11. The input power to CM4-2 with load management. The MTG generator frequency with and without load management is compared in Fig. 14. The frequency drop of the system without load management was much larger than the frequency drop with load management, which indicated that load management was an alternative way to incorporate the pulse load into shipboard power system Total load demand (a) Total load demand (b) MTG generator frequency Fig. 12. Dynamic performance of the system without load management Total load demand (a) Total load demand (b) MTG generator frequency Fig. 13. Dynamic performance of the system with load management.

8 MTG frequency without load management MTG frequency with load management Fig. 14. MTG generator frequency comparison with and without load management. V. SUMMARY In section IV, the dynamic load management method was illustrated considering available power source capacity constraint and CM4 capacity constraint. Moreover, the pulse load was also incorporated into the system through using dynamic load management method. In case 1, the available power capacity constraint was illustrated through maing the total load demand exceed the generation capacity. If the dynamic load management was not applied in the system, the MTG generator frequency would decreased from 6 Hz. After incorporating the dynamic load management method, several lower priority loads were shed to mae the available power source capacity constraint satisfied. The simulation results indicated that the system dynamic performance with load management was much better than its performance without load management. In case 2, CM4 capacity constraint was studied. When the CM4 served more than 2 MW loads, the CM4 capacity constraint would be violated. The dynamic load management method was applied to shed some non-vital load to mae the constraint satisfied. In case 3, a pulse load was incorporated into the system. When the pulse load was served, the available power source capacity constraint was violated. In order to solve the problem, dynamic load management method was used to shed some propulsion load to eliminate the constraint violation. Simulation results indicated that the MTG generation frequency drop of the system with load management was much less than that without load management. VI. CONCLUSIONS AND FUTURE WORK A simplified notional shipboard power system model was introduced to illustrate the performance of a new dynamic load management method where balances power generation and load demand of the system in real-time. The method and model were simulated in SCAD. The simulation results were compared considering available power source capacity constraint and CM4 capacity constraint. Further, a pulse load was incorporated into the system. Through using dynamic load management, pulse load was incorporated into the system successfully without violating any constraint of the system. The simulation results indicated that the dynamic load management could imize the energized loads without violating any system constraints in real-time. The system dynamic performance was much better than its performance without load management. Further research wor for the dynamic load management includes developing a multi-agent system based on the dynamic load management method to achieve the load balancing in real-time without violating system operating constraints. VII. REFERENCES [1] C. J. Dafis, "An observability formulation for nonlinear power systems modeled as differential algebraic systems," h.d. dissertation, Dept. Electrical Eng., Drexel Univ., hiladelphia, 25. [2] S. Khushalani and N. N. Schulz, "Restoration optimization with distributed generation considering islanding," in roc. 25 IEEE ower Engineering Society General Meeting, pp [3] A. I. Cohen and C. C. Wang, "An optimization method for load management scheduling," IEEE Trans. ower Systems, vol. 3, pp , May [4] K. H. Ng and G. B. Sheble, "Direct load control-a profit-based load management using linear programming," IEEE Trans. ower Systems, vol. 13, pp , May [5] H. R. Lu and L. Yao, "On-line load optimization for two way load management system," in roc. 26 IEEE International Conference on Systems, Man and Cybernetics, pp [6] K. L. Butler-urry, N. D. R. Sarma and I. V. Hics, "Service restoration in naval shipboard power systems," IEE roc. Gener. Transm. Distrib., vol. 151, pp , Jan.. [7] K. L. Butler-urry and N. D. R. Sarma, "Self-healing reconfiguration for restoration of naval shipboard power systems," IEEE Trans. ower Systems, vol. 19, pp , May. [8] C. O. Nwanpa and R. M. Hassan, "A stochastic based voltage collapse indicator," IEEE Trans. ower Systems, vol. 8, pp , Aug [9] T. Nagata and H. Sasai, "A multi-agent approach to power system restoration," IEEE Trans. ower Systems, vol. 17, pp , May 22. VIII. BIOGRAHIES Xianyong Feng (S 8) received his B.S. degree in Electrical Engineering in 25 from Harbin Institute of Technology in China. He received his M.S. degree in Automation in 28 from the University of Science and Technology of China. He joined the h.d. program in Electrical Engineering at Texas A&M University in 28. His research interests are in multi-agent system based dynamic load management for shipboard power system. Tais Zourntos (SM 9) received the B.S., M.S., and h.d. degrees in Electrical and Computer Engineering from the University of Toronto, Toronto, ON, Canada, in 1993, 1995, and 23, respectively. He is currently an Assistant rofessor in Electrical and Computer Engineering at Texas A&M University. His research is centered on the application of nonlinear systems and control theory to a wide range of problems, including behavior generation for autonomous agents, integrated analog circuits, and signal processing. Karen L. Butler-urry (SM 1) received her B.S. (summa cum laude) in Electrical Engineering in 1985 from Southern University in Baton Rouge, Louisiana. She was awarded her M.S. degree in 1987 from the University of Texas at Austin and her h.d. in Electrical Engineering in 1994 from Howard University in Washington, D.C. She joined Texas A&M University in 1994, where she currently serves as Associate Head and rofessor in the Department of Electrical and Computer Engineering. Her research interests are in the areas of distribution automation and intelligent systems for power quality, equipment deterioration, and fault diagnosis. Salman Mashayeh (S 9) received his B.S. and M.S. in Electrical ower Systems from University of Tehran, Iran, in 26 and 28, respectively. He joined ower System Automation Lab in Texas A&M University as a hd student in 28. His research interests are in power system management for next generation of Integrated Shipboard ower Systems. His job focuses on contingency analysis, dynamic stability and security studies, and other power management system requirements.